{
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   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "\n",
       "            require.config({\n",
       "                paths: {\n",
       "                    DT: '//cdn.datatables.net/1.10.20/js/jquery.dataTables.min',\n",
       "                }\n",
       "            });\n",
       "            $('head').append('<link rel=\"stylesheet\" type=\"text/css\" href=\"//cdn.datatables.net/1.10.20/css/jquery.dataTables.min.css\">');\n",
       "            $('head').append('<style> td, th {{text-align: center;}}</style>')\n",
       "        "
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import xalpha as xa\n",
    "import pandas as pd\n",
    "\n",
    "xa.set_display(\"notebook\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 指数与基金信息"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 指数信息类"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "zzhli = xa.indexinfo(\"0000922\")\n",
    "# 指数注意需要给定的代码为七位，第一位数字代表市场情况，0 代表沪市， 1 代表深市\n",
    "# 本例即为沪市 000922 的指数获取，对应中证红利指数\n",
    "# 也可直接 xa.indexinfo(\"SH000922\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>date</th>\n",
       "      <th>netvalue</th>\n",
       "      <th>totvalue</th>\n",
       "      <th>comment</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>2020-04-13</td>\n",
       "      <td>4.087991</td>\n",
       "      <td>4012.5881</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2020-04-14</td>\n",
       "      <td>4.140072</td>\n",
       "      <td>4063.7087</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2020-04-15</td>\n",
       "      <td>4.117336</td>\n",
       "      <td>4041.3918</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2020-04-16</td>\n",
       "      <td>4.104713</td>\n",
       "      <td>4029.0020</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2020-04-17</td>\n",
       "      <td>4.116853</td>\n",
       "      <td>4040.9176</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2020-04-20</td>\n",
       "      <td>4.140688</td>\n",
       "      <td>4064.3126</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2020-04-21</td>\n",
       "      <td>4.115617</td>\n",
       "      <td>4039.7047</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2020-04-22</td>\n",
       "      <td>4.132669</td>\n",
       "      <td>4056.4417</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2020-04-23</td>\n",
       "      <td>4.119847</td>\n",
       "      <td>4043.8565</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2020-04-24</td>\n",
       "      <td>4.094951</td>\n",
       "      <td>4019.4197</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2020-04-27</td>\n",
       "      <td>4.118960</td>\n",
       "      <td>4042.9854</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>`);\n",
       "\n",
       "                require([\"DT\"], function(DT) {$(document).ready( () => {\n",
       "                    // Turn existing table into datatable\n",
       "                    $(element).find(\"table.dataframe\").DataTable({'scrollX': '100%'});\n",
       "                    })\n",
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       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>netvalue</th>\n",
       "      <th>totvalue</th>\n",
       "      <th>comment</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3711</th>\n",
       "      <td>2020-04-13</td>\n",
       "      <td>4.087991</td>\n",
       "      <td>4012.5881</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3712</th>\n",
       "      <td>2020-04-14</td>\n",
       "      <td>4.140072</td>\n",
       "      <td>4063.7087</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3713</th>\n",
       "      <td>2020-04-15</td>\n",
       "      <td>4.117336</td>\n",
       "      <td>4041.3918</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3714</th>\n",
       "      <td>2020-04-16</td>\n",
       "      <td>4.104713</td>\n",
       "      <td>4029.0020</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3715</th>\n",
       "      <td>2020-04-17</td>\n",
       "      <td>4.116853</td>\n",
       "      <td>4040.9176</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3716</th>\n",
       "      <td>2020-04-20</td>\n",
       "      <td>4.140688</td>\n",
       "      <td>4064.3126</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3717</th>\n",
       "      <td>2020-04-21</td>\n",
       "      <td>4.115617</td>\n",
       "      <td>4039.7047</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3718</th>\n",
       "      <td>2020-04-22</td>\n",
       "      <td>4.132669</td>\n",
       "      <td>4056.4417</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3719</th>\n",
       "      <td>2020-04-23</td>\n",
       "      <td>4.119847</td>\n",
       "      <td>4043.8565</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3720</th>\n",
       "      <td>2020-04-24</td>\n",
       "      <td>4.094951</td>\n",
       "      <td>4019.4197</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3721</th>\n",
       "      <td>2020-04-27</td>\n",
       "      <td>4.118960</td>\n",
       "      <td>4042.9854</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           date  netvalue   totvalue  comment\n",
       "3711 2020-04-13  4.087991  4012.5881        0\n",
       "3712 2020-04-14  4.140072  4063.7087        0\n",
       "3713 2020-04-15  4.117336  4041.3918        0\n",
       "3714 2020-04-16  4.104713  4029.0020        0\n",
       "3715 2020-04-17  4.116853  4040.9176        0\n",
       "3716 2020-04-20  4.140688  4064.3126        0\n",
       "3717 2020-04-21  4.115617  4039.7047        0\n",
       "3718 2020-04-22  4.132669  4056.4417        0\n",
       "3719 2020-04-23  4.119847  4043.8565        0\n",
       "3720 2020-04-24  4.094951  4019.4197        0\n",
       "3721 2020-04-27  4.118960  4042.9854        0"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zzhli.price[zzhli.price[\"date\"] >= \"2020-04-11\"]\n",
    "# 指数的价格表，数据类型为 pandas.DataFrame, 净值栏为初始值归一化的1的值，总值栏对应指数的真实值，注释栏均为空"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('中证红利', '0000922')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zzhli.name, zzhli.code  # 指数类的部分属性"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "zzhli.bcmkset(xa.indexinfo(\"SH000300\"), start=\"2014-01-01\")\n",
    "# 设定中证红利的比较基准为沪深300指数，以便于接下来更多量化分析\n",
    "# 同时设定比较分析的区间段是从13年开始的"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
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       "                \"2014-06-11\",\n",
       "                \"2014-06-12\",\n",
       "                \"2014-06-13\",\n",
       "                \"2014-06-16\",\n",
       "                \"2014-06-17\",\n",
       "                \"2014-06-18\",\n",
       "                \"2014-06-19\",\n",
       "                \"2014-06-20\",\n",
       "                \"2014-06-23\",\n",
       "                \"2014-06-24\",\n",
       "                \"2014-06-25\",\n",
       "                \"2014-06-26\",\n",
       "                \"2014-06-27\",\n",
       "                \"2014-06-30\",\n",
       "                \"2014-07-01\",\n",
       "                \"2014-07-02\",\n",
       "                \"2014-07-03\",\n",
       "                \"2014-07-04\",\n",
       "                \"2014-07-07\",\n",
       "                \"2014-07-08\",\n",
       "                \"2014-07-09\",\n",
       "                \"2014-07-10\",\n",
       "                \"2014-07-11\",\n",
       "                \"2014-07-14\",\n",
       "                \"2014-07-15\",\n",
       "                \"2014-07-16\",\n",
       "                \"2014-07-17\",\n",
       "                \"2014-07-18\",\n",
       "                \"2014-07-21\",\n",
       "                \"2014-07-22\",\n",
       "                \"2014-07-23\",\n",
       "                \"2014-07-24\",\n",
       "                \"2014-07-25\",\n",
       "                \"2014-07-28\",\n",
       "                \"2014-07-29\",\n",
       "                \"2014-07-30\",\n",
       "                \"2014-07-31\",\n",
       "                \"2014-08-01\",\n",
       "                \"2014-08-04\",\n",
       "                \"2014-08-05\",\n",
       "                \"2014-08-06\",\n",
       "                \"2014-08-07\",\n",
       "                \"2014-08-08\",\n",
       "                \"2014-08-11\",\n",
       "                \"2014-08-12\",\n",
       "                \"2014-08-13\",\n",
       "                \"2014-08-14\",\n",
       "                \"2014-08-15\",\n",
       "                \"2014-08-18\",\n",
       "                \"2014-08-19\",\n",
       "                \"2014-08-20\",\n",
       "                \"2014-08-21\",\n",
       "                \"2014-08-22\",\n",
       "                \"2014-08-25\",\n",
       "                \"2014-08-26\",\n",
       "                \"2014-08-27\",\n",
       "                \"2014-08-28\",\n",
       "                \"2014-08-29\",\n",
       "                \"2014-09-01\",\n",
       "                \"2014-09-02\",\n",
       "                \"2014-09-03\",\n",
       "                \"2014-09-04\",\n",
       "                \"2014-09-05\",\n",
       "                \"2014-09-09\",\n",
       "                \"2014-09-10\",\n",
       "                \"2014-09-11\",\n",
       "                \"2014-09-12\",\n",
       "                \"2014-09-15\",\n",
       "                \"2014-09-16\",\n",
       "                \"2014-09-17\",\n",
       "                \"2014-09-18\",\n",
       "                \"2014-09-19\",\n",
       "                \"2014-09-22\",\n",
       "                \"2014-09-23\",\n",
       "                \"2014-09-24\",\n",
       "                \"2014-09-25\",\n",
       "                \"2014-09-26\",\n",
       "                \"2014-09-29\",\n",
       "                \"2014-09-30\",\n",
       "                \"2014-10-08\",\n",
       "                \"2014-10-09\",\n",
       "                \"2014-10-10\",\n",
       "                \"2014-10-13\",\n",
       "                \"2014-10-14\",\n",
       "                \"2014-10-15\",\n",
       "                \"2014-10-16\",\n",
       "                \"2014-10-17\",\n",
       "                \"2014-10-20\",\n",
       "                \"2014-10-21\",\n",
       "                \"2014-10-22\",\n",
       "                \"2014-10-23\",\n",
       "                \"2014-10-24\",\n",
       "                \"2014-10-27\",\n",
       "                \"2014-10-28\",\n",
       "                \"2014-10-29\",\n",
       "                \"2014-10-30\",\n",
       "                \"2014-10-31\",\n",
       "                \"2014-11-03\",\n",
       "                \"2014-11-04\",\n",
       "                \"2014-11-05\",\n",
       "                \"2014-11-06\",\n",
       "                \"2014-11-07\",\n",
       "                \"2014-11-10\",\n",
       "                \"2014-11-11\",\n",
       "                \"2014-11-12\",\n",
       "                \"2014-11-13\",\n",
       "                \"2014-11-14\",\n",
       "                \"2014-11-17\",\n",
       "                \"2014-11-18\",\n",
       "                \"2014-11-19\",\n",
       "                \"2014-11-20\",\n",
       "                \"2014-11-21\",\n",
       "                \"2014-11-24\",\n",
       "                \"2014-11-25\",\n",
       "                \"2014-11-26\",\n",
       "                \"2014-11-27\",\n",
       "                \"2014-11-28\",\n",
       "                \"2014-12-01\",\n",
       "                \"2014-12-02\",\n",
       "                \"2014-12-03\",\n",
       "                \"2014-12-04\",\n",
       "                \"2014-12-05\",\n",
       "                \"2014-12-08\",\n",
       "                \"2014-12-09\",\n",
       "                \"2014-12-10\",\n",
       "                \"2014-12-11\",\n",
       "                \"2014-12-12\",\n",
       "                \"2014-12-15\",\n",
       "                \"2014-12-16\",\n",
       "                \"2014-12-17\",\n",
       "                \"2014-12-18\",\n",
       "                \"2014-12-19\",\n",
       "                \"2014-12-22\",\n",
       "                \"2014-12-23\",\n",
       "                \"2014-12-24\",\n",
       "                \"2014-12-25\",\n",
       "                \"2014-12-26\",\n",
       "                \"2014-12-29\",\n",
       "                \"2014-12-30\",\n",
       "                \"2014-12-31\",\n",
       "                \"2015-01-05\",\n",
       "                \"2015-01-06\",\n",
       "                \"2015-01-07\",\n",
       "                \"2015-01-08\",\n",
       "                \"2015-01-09\",\n",
       "                \"2015-01-12\",\n",
       "                \"2015-01-13\",\n",
       "                \"2015-01-14\",\n",
       "                \"2015-01-15\",\n",
       "                \"2015-01-16\",\n",
       "                \"2015-01-19\",\n",
       "                \"2015-01-20\",\n",
       "                \"2015-01-21\",\n",
       "                \"2015-01-22\",\n",
       "                \"2015-01-23\",\n",
       "                \"2015-01-26\",\n",
       "                \"2015-01-27\",\n",
       "                \"2015-01-28\",\n",
       "                \"2015-01-29\",\n",
       "                \"2015-01-30\",\n",
       "                \"2015-02-02\",\n",
       "                \"2015-02-03\",\n",
       "                \"2015-02-04\",\n",
       "                \"2015-02-05\",\n",
       "                \"2015-02-06\",\n",
       "                \"2015-02-09\",\n",
       "                \"2015-02-10\",\n",
       "                \"2015-02-11\",\n",
       "                \"2015-02-12\",\n",
       "                \"2015-02-13\",\n",
       "                \"2015-02-16\",\n",
       "                \"2015-02-17\",\n",
       "                \"2015-02-25\",\n",
       "                \"2015-02-26\",\n",
       "                \"2015-02-27\",\n",
       "                \"2015-03-02\",\n",
       "                \"2015-03-03\",\n",
       "                \"2015-03-04\",\n",
       "                \"2015-03-05\",\n",
       "                \"2015-03-06\",\n",
       "                \"2015-03-09\",\n",
       "                \"2015-03-10\",\n",
       "                \"2015-03-11\",\n",
       "                \"2015-03-12\",\n",
       "                \"2015-03-13\",\n",
       "                \"2015-03-16\",\n",
       "                \"2015-03-17\",\n",
       "                \"2015-03-18\",\n",
       "                \"2015-03-19\",\n",
       "                \"2015-03-20\",\n",
       "                \"2015-03-23\",\n",
       "                \"2015-03-24\",\n",
       "                \"2015-03-25\",\n",
       "                \"2015-03-26\",\n",
       "                \"2015-03-27\",\n",
       "                \"2015-03-30\",\n",
       "                \"2015-03-31\",\n",
       "                \"2015-04-01\",\n",
       "                \"2015-04-02\",\n",
       "                \"2015-04-03\",\n",
       "                \"2015-04-07\",\n",
       "                \"2015-04-08\",\n",
       "                \"2015-04-09\",\n",
       "                \"2015-04-10\",\n",
       "                \"2015-04-13\",\n",
       "                \"2015-04-14\",\n",
       "                \"2015-04-15\",\n",
       "                \"2015-04-16\",\n",
       "                \"2015-04-17\",\n",
       "                \"2015-04-20\",\n",
       "                \"2015-04-21\",\n",
       "                \"2015-04-22\",\n",
       "                \"2015-04-23\",\n",
       "                \"2015-04-24\",\n",
       "                \"2015-04-27\",\n",
       "                \"2015-04-28\",\n",
       "                \"2015-04-29\",\n",
       "                \"2015-04-30\",\n",
       "                \"2015-05-04\",\n",
       "                \"2015-05-05\",\n",
       "                \"2015-05-06\",\n",
       "                \"2015-05-07\",\n",
       "                \"2015-05-08\",\n",
       "                \"2015-05-11\",\n",
       "                \"2015-05-12\",\n",
       "                \"2015-05-13\",\n",
       "                \"2015-05-14\",\n",
       "                \"2015-05-15\",\n",
       "                \"2015-05-18\",\n",
       "                \"2015-05-19\",\n",
       "                \"2015-05-20\",\n",
       "                \"2015-05-21\",\n",
       "                \"2015-05-22\",\n",
       "                \"2015-05-25\",\n",
       "                \"2015-05-26\",\n",
       "                \"2015-05-27\",\n",
       "                \"2015-05-28\",\n",
       "                \"2015-05-29\",\n",
       "                \"2015-06-01\",\n",
       "                \"2015-06-02\",\n",
       "                \"2015-06-03\",\n",
       "                \"2015-06-04\",\n",
       "                \"2015-06-05\",\n",
       "                \"2015-06-08\",\n",
       "                \"2015-06-09\",\n",
       "                \"2015-06-10\",\n",
       "                \"2015-06-11\",\n",
       "                \"2015-06-12\",\n",
       "                \"2015-06-15\",\n",
       "                \"2015-06-16\",\n",
       "                \"2015-06-17\",\n",
       "                \"2015-06-18\",\n",
       "                \"2015-06-19\",\n",
       "                \"2015-06-23\",\n",
       "                \"2015-06-24\",\n",
       "                \"2015-06-25\",\n",
       "                \"2015-06-26\",\n",
       "                \"2015-06-29\",\n",
       "                \"2015-06-30\",\n",
       "                \"2015-07-01\",\n",
       "                \"2015-07-02\",\n",
       "                \"2015-07-03\",\n",
       "                \"2015-07-06\",\n",
       "                \"2015-07-07\",\n",
       "                \"2015-07-08\",\n",
       "                \"2015-07-09\",\n",
       "                \"2015-07-10\",\n",
       "                \"2015-07-13\",\n",
       "                \"2015-07-14\",\n",
       "                \"2015-07-15\",\n",
       "                \"2015-07-16\",\n",
       "                \"2015-07-17\",\n",
       "                \"2015-07-20\",\n",
       "                \"2015-07-21\",\n",
       "                \"2015-07-22\",\n",
       "                \"2015-07-23\",\n",
       "                \"2015-07-24\",\n",
       "                \"2015-07-27\",\n",
       "                \"2015-07-28\",\n",
       "                \"2015-07-29\",\n",
       "                \"2015-07-30\",\n",
       "                \"2015-07-31\",\n",
       "                \"2015-08-03\",\n",
       "                \"2015-08-04\",\n",
       "                \"2015-08-05\",\n",
       "                \"2015-08-06\",\n",
       "                \"2015-08-07\",\n",
       "                \"2015-08-10\",\n",
       "                \"2015-08-11\",\n",
       "                \"2015-08-12\",\n",
       "                \"2015-08-13\",\n",
       "                \"2015-08-14\",\n",
       "                \"2015-08-17\",\n",
       "                \"2015-08-18\",\n",
       "                \"2015-08-19\",\n",
       "                \"2015-08-20\",\n",
       "                \"2015-08-21\",\n",
       "                \"2015-08-24\",\n",
       "                \"2015-08-25\",\n",
       "                \"2015-08-26\",\n",
       "                \"2015-08-27\",\n",
       "                \"2015-08-28\",\n",
       "                \"2015-08-31\",\n",
       "                \"2015-09-01\",\n",
       "                \"2015-09-02\",\n",
       "                \"2015-09-07\",\n",
       "                \"2015-09-08\",\n",
       "                \"2015-09-09\",\n",
       "                \"2015-09-10\",\n",
       "                \"2015-09-11\",\n",
       "                \"2015-09-14\",\n",
       "                \"2015-09-15\",\n",
       "                \"2015-09-16\",\n",
       "                \"2015-09-17\",\n",
       "                \"2015-09-18\",\n",
       "                \"2015-09-21\",\n",
       "                \"2015-09-22\",\n",
       "                \"2015-09-23\",\n",
       "                \"2015-09-24\",\n",
       "                \"2015-09-25\",\n",
       "                \"2015-09-28\",\n",
       "                \"2015-09-29\",\n",
       "                \"2015-09-30\",\n",
       "                \"2015-10-08\",\n",
       "                \"2015-10-09\",\n",
       "                \"2015-10-12\",\n",
       "                \"2015-10-13\",\n",
       "                \"2015-10-14\",\n",
       "                \"2015-10-15\",\n",
       "                \"2015-10-16\",\n",
       "                \"2015-10-19\",\n",
       "                \"2015-10-20\",\n",
       "                \"2015-10-21\",\n",
       "                \"2015-10-22\",\n",
       "                \"2015-10-23\",\n",
       "                \"2015-10-26\",\n",
       "                \"2015-10-27\",\n",
       "                \"2015-10-28\",\n",
       "                \"2015-10-29\",\n",
       "                \"2015-10-30\",\n",
       "                \"2015-11-02\",\n",
       "                \"2015-11-03\",\n",
       "                \"2015-11-04\",\n",
       "                \"2015-11-05\",\n",
       "                \"2015-11-06\",\n",
       "                \"2015-11-09\",\n",
       "                \"2015-11-10\",\n",
       "                \"2015-11-11\",\n",
       "                \"2015-11-12\",\n",
       "                \"2015-11-13\",\n",
       "                \"2015-11-16\",\n",
       "                \"2015-11-17\",\n",
       "                \"2015-11-18\",\n",
       "                \"2015-11-19\",\n",
       "                \"2015-11-20\",\n",
       "                \"2015-11-23\",\n",
       "                \"2015-11-24\",\n",
       "                \"2015-11-25\",\n",
       "                \"2015-11-26\",\n",
       "                \"2015-11-27\",\n",
       "                \"2015-11-30\",\n",
       "                \"2015-12-01\",\n",
       "                \"2015-12-02\",\n",
       "                \"2015-12-03\",\n",
       "                \"2015-12-04\",\n",
       "                \"2015-12-07\",\n",
       "                \"2015-12-08\",\n",
       "                \"2015-12-09\",\n",
       "                \"2015-12-10\",\n",
       "                \"2015-12-11\",\n",
       "                \"2015-12-14\",\n",
       "                \"2015-12-15\",\n",
       "                \"2015-12-16\",\n",
       "                \"2015-12-17\",\n",
       "                \"2015-12-18\",\n",
       "                \"2015-12-21\",\n",
       "                \"2015-12-22\",\n",
       "                \"2015-12-23\",\n",
       "                \"2015-12-24\",\n",
       "                \"2015-12-25\",\n",
       "                \"2015-12-28\",\n",
       "                \"2015-12-29\",\n",
       "                \"2015-12-30\",\n",
       "                \"2015-12-31\",\n",
       "                \"2016-01-04\",\n",
       "                \"2016-01-05\",\n",
       "                \"2016-01-06\",\n",
       "                \"2016-01-07\",\n",
       "                \"2016-01-08\",\n",
       "                \"2016-01-11\",\n",
       "                \"2016-01-12\",\n",
       "                \"2016-01-13\",\n",
       "                \"2016-01-14\",\n",
       "                \"2016-01-15\",\n",
       "                \"2016-01-18\",\n",
       "                \"2016-01-19\",\n",
       "                \"2016-01-20\",\n",
       "                \"2016-01-21\",\n",
       "                \"2016-01-22\",\n",
       "                \"2016-01-25\",\n",
       "                \"2016-01-26\",\n",
       "                \"2016-01-27\",\n",
       "                \"2016-01-28\",\n",
       "                \"2016-01-29\",\n",
       "                \"2016-02-01\",\n",
       "                \"2016-02-02\",\n",
       "                \"2016-02-03\",\n",
       "                \"2016-02-04\",\n",
       "                \"2016-02-05\",\n",
       "                \"2016-02-15\",\n",
       "                \"2016-02-16\",\n",
       "                \"2016-02-17\",\n",
       "                \"2016-02-18\",\n",
       "                \"2016-02-19\",\n",
       "                \"2016-02-22\",\n",
       "                \"2016-02-23\",\n",
       "                \"2016-02-24\",\n",
       "                \"2016-02-25\",\n",
       "                \"2016-02-26\",\n",
       "                \"2016-02-29\",\n",
       "                \"2016-03-01\",\n",
       "                \"2016-03-02\",\n",
       "                \"2016-03-03\",\n",
       "                \"2016-03-04\",\n",
       "                \"2016-03-07\",\n",
       "                \"2016-03-08\",\n",
       "                \"2016-03-09\",\n",
       "                \"2016-03-10\",\n",
       "                \"2016-03-11\",\n",
       "                \"2016-03-14\",\n",
       "                \"2016-03-15\",\n",
       "                \"2016-03-16\",\n",
       "                \"2016-03-17\",\n",
       "                \"2016-03-18\",\n",
       "                \"2016-03-21\",\n",
       "                \"2016-03-22\",\n",
       "                \"2016-03-23\",\n",
       "                \"2016-03-24\",\n",
       "                \"2016-03-25\",\n",
       "                \"2016-03-28\",\n",
       "                \"2016-03-29\",\n",
       "                \"2016-03-30\",\n",
       "                \"2016-03-31\",\n",
       "                \"2016-04-01\",\n",
       "                \"2016-04-05\",\n",
       "                \"2016-04-06\",\n",
       "                \"2016-04-07\",\n",
       "                \"2016-04-08\",\n",
       "                \"2016-04-11\",\n",
       "                \"2016-04-12\",\n",
       "                \"2016-04-13\",\n",
       "                \"2016-04-14\",\n",
       "                \"2016-04-15\",\n",
       "                \"2016-04-18\",\n",
       "                \"2016-04-19\",\n",
       "                \"2016-04-20\",\n",
       "                \"2016-04-21\",\n",
       "                \"2016-04-22\",\n",
       "                \"2016-04-25\",\n",
       "                \"2016-04-26\",\n",
       "                \"2016-04-27\",\n",
       "                \"2016-04-28\",\n",
       "                \"2016-04-29\",\n",
       "                \"2016-05-03\",\n",
       "                \"2016-05-04\",\n",
       "                \"2016-05-05\",\n",
       "                \"2016-05-06\",\n",
       "                \"2016-05-09\",\n",
       "                \"2016-05-10\",\n",
       "                \"2016-05-11\",\n",
       "                \"2016-05-12\",\n",
       "                \"2016-05-13\",\n",
       "                \"2016-05-16\",\n",
       "                \"2016-05-17\",\n",
       "                \"2016-05-18\",\n",
       "                \"2016-05-19\",\n",
       "                \"2016-05-20\",\n",
       "                \"2016-05-23\",\n",
       "                \"2016-05-24\",\n",
       "                \"2016-05-25\",\n",
       "                \"2016-05-26\",\n",
       "                \"2016-05-27\",\n",
       "                \"2016-05-30\",\n",
       "                \"2016-05-31\",\n",
       "                \"2016-06-01\",\n",
       "                \"2016-06-02\",\n",
       "                \"2016-06-03\",\n",
       "                \"2016-06-06\",\n",
       "                \"2016-06-07\",\n",
       "                \"2016-06-08\",\n",
       "                \"2016-06-13\",\n",
       "                \"2016-06-14\",\n",
       "                \"2016-06-15\",\n",
       "                \"2016-06-16\",\n",
       "                \"2016-06-17\",\n",
       "                \"2016-06-20\",\n",
       "                \"2016-06-21\",\n",
       "                \"2016-06-22\",\n",
       "                \"2016-06-23\",\n",
       "                \"2016-06-24\",\n",
       "                \"2016-06-27\",\n",
       "                \"2016-06-28\",\n",
       "                \"2016-06-29\",\n",
       "                \"2016-06-30\",\n",
       "                \"2016-07-01\",\n",
       "                \"2016-07-04\",\n",
       "                \"2016-07-05\",\n",
       "                \"2016-07-06\",\n",
       "                \"2016-07-07\",\n",
       "                \"2016-07-08\",\n",
       "                \"2016-07-11\",\n",
       "                \"2016-07-12\",\n",
       "                \"2016-07-13\",\n",
       "                \"2016-07-14\",\n",
       "                \"2016-07-15\",\n",
       "                \"2016-07-18\",\n",
       "                \"2016-07-19\",\n",
       "                \"2016-07-20\",\n",
       "                \"2016-07-21\",\n",
       "                \"2016-07-22\",\n",
       "                \"2016-07-25\",\n",
       "                \"2016-07-26\",\n",
       "                \"2016-07-27\",\n",
       "                \"2016-07-28\",\n",
       "                \"2016-07-29\",\n",
       "                \"2016-08-01\",\n",
       "                \"2016-08-02\",\n",
       "                \"2016-08-03\",\n",
       "                \"2016-08-04\",\n",
       "                \"2016-08-05\",\n",
       "                \"2016-08-08\",\n",
       "                \"2016-08-09\",\n",
       "                \"2016-08-10\",\n",
       "                \"2016-08-11\",\n",
       "                \"2016-08-12\",\n",
       "                \"2016-08-15\",\n",
       "                \"2016-08-16\",\n",
       "                \"2016-08-17\",\n",
       "                \"2016-08-18\",\n",
       "                \"2016-08-19\",\n",
       "                \"2016-08-22\",\n",
       "                \"2016-08-23\",\n",
       "                \"2016-08-24\",\n",
       "                \"2016-08-25\",\n",
       "                \"2016-08-26\",\n",
       "                \"2016-08-29\",\n",
       "                \"2016-08-30\",\n",
       "                \"2016-08-31\",\n",
       "                \"2016-09-01\",\n",
       "                \"2016-09-02\",\n",
       "                \"2016-09-05\",\n",
       "                \"2016-09-06\",\n",
       "                \"2016-09-07\",\n",
       "                \"2016-09-08\",\n",
       "                \"2016-09-09\",\n",
       "                \"2016-09-12\",\n",
       "                \"2016-09-13\",\n",
       "                \"2016-09-14\",\n",
       "                \"2016-09-19\",\n",
       "                \"2016-09-20\",\n",
       "                \"2016-09-21\",\n",
       "                \"2016-09-22\",\n",
       "                \"2016-09-23\",\n",
       "                \"2016-09-26\",\n",
       "                \"2016-09-27\",\n",
       "                \"2016-09-28\",\n",
       "                \"2016-09-29\",\n",
       "                \"2016-09-30\",\n",
       "                \"2016-10-10\",\n",
       "                \"2016-10-11\",\n",
       "                \"2016-10-12\",\n",
       "                \"2016-10-13\",\n",
       "                \"2016-10-14\",\n",
       "                \"2016-10-17\",\n",
       "                \"2016-10-18\",\n",
       "                \"2016-10-19\",\n",
       "                \"2016-10-20\",\n",
       "                \"2016-10-21\",\n",
       "                \"2016-10-24\",\n",
       "                \"2016-10-25\",\n",
       "                \"2016-10-26\",\n",
       "                \"2016-10-27\",\n",
       "                \"2016-10-28\",\n",
       "                \"2016-10-31\",\n",
       "                \"2016-11-01\",\n",
       "                \"2016-11-02\",\n",
       "                \"2016-11-03\",\n",
       "                \"2016-11-04\",\n",
       "                \"2016-11-07\",\n",
       "                \"2016-11-08\",\n",
       "                \"2016-11-09\",\n",
       "                \"2016-11-10\",\n",
       "                \"2016-11-11\",\n",
       "                \"2016-11-14\",\n",
       "                \"2016-11-15\",\n",
       "                \"2016-11-16\",\n",
       "                \"2016-11-17\",\n",
       "                \"2016-11-18\",\n",
       "                \"2016-11-21\",\n",
       "                \"2016-11-22\",\n",
       "                \"2016-11-23\",\n",
       "                \"2016-11-24\",\n",
       "                \"2016-11-25\",\n",
       "                \"2016-11-28\",\n",
       "                \"2016-11-29\",\n",
       "                \"2016-11-30\",\n",
       "                \"2016-12-01\",\n",
       "                \"2016-12-02\",\n",
       "                \"2016-12-05\",\n",
       "                \"2016-12-06\",\n",
       "                \"2016-12-07\",\n",
       "                \"2016-12-08\",\n",
       "                \"2016-12-09\",\n",
       "                \"2016-12-12\",\n",
       "                \"2016-12-13\",\n",
       "                \"2016-12-14\",\n",
       "                \"2016-12-15\",\n",
       "                \"2016-12-16\",\n",
       "                \"2016-12-19\",\n",
       "                \"2016-12-20\",\n",
       "                \"2016-12-21\",\n",
       "                \"2016-12-22\",\n",
       "                \"2016-12-23\",\n",
       "                \"2016-12-26\",\n",
       "                \"2016-12-27\",\n",
       "                \"2016-12-28\",\n",
       "                \"2016-12-29\",\n",
       "                \"2016-12-30\",\n",
       "                \"2017-01-03\",\n",
       "                \"2017-01-04\",\n",
       "                \"2017-01-05\",\n",
       "                \"2017-01-06\",\n",
       "                \"2017-01-09\",\n",
       "                \"2017-01-10\",\n",
       "                \"2017-01-11\",\n",
       "                \"2017-01-12\",\n",
       "                \"2017-01-13\",\n",
       "                \"2017-01-16\",\n",
       "                \"2017-01-17\",\n",
       "                \"2017-01-18\",\n",
       "                \"2017-01-19\",\n",
       "                \"2017-01-20\",\n",
       "                \"2017-01-23\",\n",
       "                \"2017-01-24\",\n",
       "                \"2017-01-25\",\n",
       "                \"2017-01-26\",\n",
       "                \"2017-02-03\",\n",
       "                \"2017-02-06\",\n",
       "                \"2017-02-07\",\n",
       "                \"2017-02-08\",\n",
       "                \"2017-02-09\",\n",
       "                \"2017-02-10\",\n",
       "                \"2017-02-13\",\n",
       "                \"2017-02-14\",\n",
       "                \"2017-02-15\",\n",
       "                \"2017-02-16\",\n",
       "                \"2017-02-17\",\n",
       "                \"2017-02-20\",\n",
       "                \"2017-02-21\",\n",
       "                \"2017-02-22\",\n",
       "                \"2017-02-23\",\n",
       "                \"2017-02-24\",\n",
       "                \"2017-02-27\",\n",
       "                \"2017-02-28\",\n",
       "                \"2017-03-01\",\n",
       "                \"2017-03-02\",\n",
       "                \"2017-03-03\",\n",
       "                \"2017-03-06\",\n",
       "                \"2017-03-07\",\n",
       "                \"2017-03-08\",\n",
       "                \"2017-03-09\",\n",
       "                \"2017-03-10\",\n",
       "                \"2017-03-13\",\n",
       "                \"2017-03-14\",\n",
       "                \"2017-03-15\",\n",
       "                \"2017-03-16\",\n",
       "                \"2017-03-17\",\n",
       "                \"2017-03-20\",\n",
       "                \"2017-03-21\",\n",
       "                \"2017-03-22\",\n",
       "                \"2017-03-23\",\n",
       "                \"2017-03-24\",\n",
       "                \"2017-03-27\",\n",
       "                \"2017-03-28\",\n",
       "                \"2017-03-29\",\n",
       "                \"2017-03-30\",\n",
       "                \"2017-03-31\",\n",
       "                \"2017-04-05\",\n",
       "                \"2017-04-06\",\n",
       "                \"2017-04-07\",\n",
       "                \"2017-04-10\",\n",
       "                \"2017-04-11\",\n",
       "                \"2017-04-12\",\n",
       "                \"2017-04-13\",\n",
       "                \"2017-04-14\",\n",
       "                \"2017-04-17\",\n",
       "                \"2017-04-18\",\n",
       "                \"2017-04-19\",\n",
       "                \"2017-04-20\",\n",
       "                \"2017-04-21\",\n",
       "                \"2017-04-24\",\n",
       "                \"2017-04-25\",\n",
       "                \"2017-04-26\",\n",
       "                \"2017-04-27\",\n",
       "                \"2017-04-28\",\n",
       "                \"2017-05-02\",\n",
       "                \"2017-05-03\",\n",
       "                \"2017-05-04\",\n",
       "                \"2017-05-05\",\n",
       "                \"2017-05-08\",\n",
       "                \"2017-05-09\",\n",
       "                \"2017-05-10\",\n",
       "                \"2017-05-11\",\n",
       "                \"2017-05-12\",\n",
       "                \"2017-05-15\",\n",
       "                \"2017-05-16\",\n",
       "                \"2017-05-17\",\n",
       "                \"2017-05-18\",\n",
       "                \"2017-05-19\",\n",
       "                \"2017-05-22\",\n",
       "                \"2017-05-23\",\n",
       "                \"2017-05-24\",\n",
       "                \"2017-05-25\",\n",
       "                \"2017-05-26\",\n",
       "                \"2017-05-31\",\n",
       "                \"2017-06-01\",\n",
       "                \"2017-06-02\",\n",
       "                \"2017-06-05\",\n",
       "                \"2017-06-06\",\n",
       "                \"2017-06-07\",\n",
       "                \"2017-06-08\",\n",
       "                \"2017-06-09\",\n",
       "                \"2017-06-12\",\n",
       "                \"2017-06-13\",\n",
       "                \"2017-06-14\",\n",
       "                \"2017-06-15\",\n",
       "                \"2017-06-16\",\n",
       "                \"2017-06-19\",\n",
       "                \"2017-06-20\",\n",
       "                \"2017-06-21\",\n",
       "                \"2017-06-22\",\n",
       "                \"2017-06-23\",\n",
       "                \"2017-06-26\",\n",
       "                \"2017-06-27\",\n",
       "                \"2017-06-28\",\n",
       "                \"2017-06-29\",\n",
       "                \"2017-06-30\",\n",
       "                \"2017-07-03\",\n",
       "                \"2017-07-04\",\n",
       "                \"2017-07-05\",\n",
       "                \"2017-07-06\",\n",
       "                \"2017-07-07\",\n",
       "                \"2017-07-10\",\n",
       "                \"2017-07-11\",\n",
       "                \"2017-07-12\",\n",
       "                \"2017-07-13\",\n",
       "                \"2017-07-14\",\n",
       "                \"2017-07-17\",\n",
       "                \"2017-07-18\",\n",
       "                \"2017-07-19\",\n",
       "                \"2017-07-20\",\n",
       "                \"2017-07-21\",\n",
       "                \"2017-07-24\",\n",
       "                \"2017-07-25\",\n",
       "                \"2017-07-26\",\n",
       "                \"2017-07-27\",\n",
       "                \"2017-07-28\",\n",
       "                \"2017-07-31\",\n",
       "                \"2017-08-01\",\n",
       "                \"2017-08-02\",\n",
       "                \"2017-08-03\",\n",
       "                \"2017-08-04\",\n",
       "                \"2017-08-07\",\n",
       "                \"2017-08-08\",\n",
       "                \"2017-08-09\",\n",
       "                \"2017-08-10\",\n",
       "                \"2017-08-11\",\n",
       "                \"2017-08-14\",\n",
       "                \"2017-08-15\",\n",
       "                \"2017-08-16\",\n",
       "                \"2017-08-17\",\n",
       "                \"2017-08-18\",\n",
       "                \"2017-08-21\",\n",
       "                \"2017-08-22\",\n",
       "                \"2017-08-23\",\n",
       "                \"2017-08-24\",\n",
       "                \"2017-08-25\",\n",
       "                \"2017-08-28\",\n",
       "                \"2017-08-29\",\n",
       "                \"2017-08-30\",\n",
       "                \"2017-08-31\",\n",
       "                \"2017-09-01\",\n",
       "                \"2017-09-04\",\n",
       "                \"2017-09-05\",\n",
       "                \"2017-09-06\",\n",
       "                \"2017-09-07\",\n",
       "                \"2017-09-08\",\n",
       "                \"2017-09-11\",\n",
       "                \"2017-09-12\",\n",
       "                \"2017-09-13\",\n",
       "                \"2017-09-14\",\n",
       "                \"2017-09-15\",\n",
       "                \"2017-09-18\",\n",
       "                \"2017-09-19\",\n",
       "                \"2017-09-20\",\n",
       "                \"2017-09-21\",\n",
       "                \"2017-09-22\",\n",
       "                \"2017-09-25\",\n",
       "                \"2017-09-26\",\n",
       "                \"2017-09-27\",\n",
       "                \"2017-09-28\",\n",
       "                \"2017-09-29\",\n",
       "                \"2017-10-09\",\n",
       "                \"2017-10-10\",\n",
       "                \"2017-10-11\",\n",
       "                \"2017-10-12\",\n",
       "                \"2017-10-13\",\n",
       "                \"2017-10-16\",\n",
       "                \"2017-10-17\",\n",
       "                \"2017-10-18\",\n",
       "                \"2017-10-19\",\n",
       "                \"2017-10-20\",\n",
       "                \"2017-10-23\",\n",
       "                \"2017-10-24\",\n",
       "                \"2017-10-25\",\n",
       "                \"2017-10-26\",\n",
       "                \"2017-10-27\",\n",
       "                \"2017-10-30\",\n",
       "                \"2017-10-31\",\n",
       "                \"2017-11-01\",\n",
       "                \"2017-11-02\",\n",
       "                \"2017-11-03\",\n",
       "                \"2017-11-06\",\n",
       "                \"2017-11-07\",\n",
       "                \"2017-11-08\",\n",
       "                \"2017-11-09\",\n",
       "                \"2017-11-10\",\n",
       "                \"2017-11-13\",\n",
       "                \"2017-11-14\",\n",
       "                \"2017-11-15\",\n",
       "                \"2017-11-16\",\n",
       "                \"2017-11-17\",\n",
       "                \"2017-11-20\",\n",
       "                \"2017-11-21\",\n",
       "                \"2017-11-22\",\n",
       "                \"2017-11-23\",\n",
       "                \"2017-11-24\",\n",
       "                \"2017-11-27\",\n",
       "                \"2017-11-28\",\n",
       "                \"2017-11-29\",\n",
       "                \"2017-11-30\",\n",
       "                \"2017-12-01\",\n",
       "                \"2017-12-04\",\n",
       "                \"2017-12-05\",\n",
       "                \"2017-12-06\",\n",
       "                \"2017-12-07\",\n",
       "                \"2017-12-08\",\n",
       "                \"2017-12-11\",\n",
       "                \"2017-12-12\",\n",
       "                \"2017-12-13\",\n",
       "                \"2017-12-14\",\n",
       "                \"2017-12-15\",\n",
       "                \"2017-12-18\",\n",
       "                \"2017-12-19\",\n",
       "                \"2017-12-20\",\n",
       "                \"2017-12-21\",\n",
       "                \"2017-12-22\",\n",
       "                \"2017-12-25\",\n",
       "                \"2017-12-26\",\n",
       "                \"2017-12-27\",\n",
       "                \"2017-12-28\",\n",
       "                \"2017-12-29\",\n",
       "                \"2018-01-02\",\n",
       "                \"2018-01-03\",\n",
       "                \"2018-01-04\",\n",
       "                \"2018-01-05\",\n",
       "                \"2018-01-08\",\n",
       "                \"2018-01-09\",\n",
       "                \"2018-01-10\",\n",
       "                \"2018-01-11\",\n",
       "                \"2018-01-12\",\n",
       "                \"2018-01-15\",\n",
       "                \"2018-01-16\",\n",
       "                \"2018-01-17\",\n",
       "                \"2018-01-18\",\n",
       "                \"2018-01-19\",\n",
       "                \"2018-01-22\",\n",
       "                \"2018-01-23\",\n",
       "                \"2018-01-24\",\n",
       "                \"2018-01-25\",\n",
       "                \"2018-01-26\",\n",
       "                \"2018-01-29\",\n",
       "                \"2018-01-30\",\n",
       "                \"2018-01-31\",\n",
       "                \"2018-02-01\",\n",
       "                \"2018-02-02\",\n",
       "                \"2018-02-05\",\n",
       "                \"2018-02-06\",\n",
       "                \"2018-02-07\",\n",
       "                \"2018-02-08\",\n",
       "                \"2018-02-09\",\n",
       "                \"2018-02-12\",\n",
       "                \"2018-02-13\",\n",
       "                \"2018-02-14\",\n",
       "                \"2018-02-22\",\n",
       "                \"2018-02-23\",\n",
       "                \"2018-02-26\",\n",
       "                \"2018-02-27\",\n",
       "                \"2018-02-28\",\n",
       "                \"2018-03-01\",\n",
       "                \"2018-03-02\",\n",
       "                \"2018-03-05\",\n",
       "                \"2018-03-06\",\n",
       "                \"2018-03-07\",\n",
       "                \"2018-03-08\",\n",
       "                \"2018-03-09\",\n",
       "                \"2018-03-12\",\n",
       "                \"2018-03-13\",\n",
       "                \"2018-03-14\",\n",
       "                \"2018-03-15\",\n",
       "                \"2018-03-16\",\n",
       "                \"2018-03-19\",\n",
       "                \"2018-03-20\",\n",
       "                \"2018-03-21\",\n",
       "                \"2018-03-22\",\n",
       "                \"2018-03-23\",\n",
       "                \"2018-03-26\",\n",
       "                \"2018-03-27\",\n",
       "                \"2018-03-28\",\n",
       "                \"2018-03-29\",\n",
       "                \"2018-03-30\",\n",
       "                \"2018-04-02\",\n",
       "                \"2018-04-03\",\n",
       "                \"2018-04-04\",\n",
       "                \"2018-04-09\",\n",
       "                \"2018-04-10\",\n",
       "                \"2018-04-11\",\n",
       "                \"2018-04-12\",\n",
       "                \"2018-04-13\",\n",
       "                \"2018-04-16\",\n",
       "                \"2018-04-17\",\n",
       "                \"2018-04-18\",\n",
       "                \"2018-04-19\",\n",
       "                \"2018-04-20\",\n",
       "                \"2018-04-23\",\n",
       "                \"2018-04-24\",\n",
       "                \"2018-04-25\",\n",
       "                \"2018-04-26\",\n",
       "                \"2018-04-27\",\n",
       "                \"2018-05-02\",\n",
       "                \"2018-05-03\",\n",
       "                \"2018-05-04\",\n",
       "                \"2018-05-07\",\n",
       "                \"2018-05-08\",\n",
       "                \"2018-05-09\",\n",
       "                \"2018-05-10\",\n",
       "                \"2018-05-11\",\n",
       "                \"2018-05-14\",\n",
       "                \"2018-05-15\",\n",
       "                \"2018-05-16\",\n",
       "                \"2018-05-17\",\n",
       "                \"2018-05-18\",\n",
       "                \"2018-05-21\",\n",
       "                \"2018-05-22\",\n",
       "                \"2018-05-23\",\n",
       "                \"2018-05-24\",\n",
       "                \"2018-05-25\",\n",
       "                \"2018-05-28\",\n",
       "                \"2018-05-29\",\n",
       "                \"2018-05-30\",\n",
       "                \"2018-05-31\",\n",
       "                \"2018-06-01\",\n",
       "                \"2018-06-04\",\n",
       "                \"2018-06-05\",\n",
       "                \"2018-06-06\",\n",
       "                \"2018-06-07\",\n",
       "                \"2018-06-08\",\n",
       "                \"2018-06-11\",\n",
       "                \"2018-06-12\",\n",
       "                \"2018-06-13\",\n",
       "                \"2018-06-14\",\n",
       "                \"2018-06-15\",\n",
       "                \"2018-06-19\",\n",
       "                \"2018-06-20\",\n",
       "                \"2018-06-21\",\n",
       "                \"2018-06-22\",\n",
       "                \"2018-06-25\",\n",
       "                \"2018-06-26\",\n",
       "                \"2018-06-27\",\n",
       "                \"2018-06-28\",\n",
       "                \"2018-06-29\",\n",
       "                \"2018-07-02\",\n",
       "                \"2018-07-03\",\n",
       "                \"2018-07-04\",\n",
       "                \"2018-07-05\",\n",
       "                \"2018-07-06\",\n",
       "                \"2018-07-09\",\n",
       "                \"2018-07-10\",\n",
       "                \"2018-07-11\",\n",
       "                \"2018-07-12\",\n",
       "                \"2018-07-13\",\n",
       "                \"2018-07-16\",\n",
       "                \"2018-07-17\",\n",
       "                \"2018-07-18\",\n",
       "                \"2018-07-19\",\n",
       "                \"2018-07-20\",\n",
       "                \"2018-07-23\",\n",
       "                \"2018-07-24\",\n",
       "                \"2018-07-25\",\n",
       "                \"2018-07-26\",\n",
       "                \"2018-07-27\",\n",
       "                \"2018-07-30\",\n",
       "                \"2018-07-31\",\n",
       "                \"2018-08-01\",\n",
       "                \"2018-08-02\",\n",
       "                \"2018-08-03\",\n",
       "                \"2018-08-06\",\n",
       "                \"2018-08-07\",\n",
       "                \"2018-08-08\",\n",
       "                \"2018-08-09\",\n",
       "                \"2018-08-10\",\n",
       "                \"2018-08-13\",\n",
       "                \"2018-08-14\",\n",
       "                \"2018-08-15\",\n",
       "                \"2018-08-16\",\n",
       "                \"2018-08-17\",\n",
       "                \"2018-08-20\",\n",
       "                \"2018-08-21\",\n",
       "                \"2018-08-22\",\n",
       "                \"2018-08-23\",\n",
       "                \"2018-08-24\",\n",
       "                \"2018-08-27\",\n",
       "                \"2018-08-28\",\n",
       "                \"2018-08-29\",\n",
       "                \"2018-08-30\",\n",
       "                \"2018-08-31\",\n",
       "                \"2018-09-03\",\n",
       "                \"2018-09-04\",\n",
       "                \"2018-09-05\",\n",
       "                \"2018-09-06\",\n",
       "                \"2018-09-07\",\n",
       "                \"2018-09-10\",\n",
       "                \"2018-09-11\",\n",
       "                \"2018-09-12\",\n",
       "                \"2018-09-13\",\n",
       "                \"2018-09-14\",\n",
       "                \"2018-09-17\",\n",
       "                \"2018-09-18\",\n",
       "                \"2018-09-19\",\n",
       "                \"2018-09-20\",\n",
       "                \"2018-09-21\",\n",
       "                \"2018-09-25\",\n",
       "                \"2018-09-26\",\n",
       "                \"2018-09-27\",\n",
       "                \"2018-09-28\",\n",
       "                \"2018-10-08\",\n",
       "                \"2018-10-09\",\n",
       "                \"2018-10-10\",\n",
       "                \"2018-10-11\",\n",
       "                \"2018-10-12\",\n",
       "                \"2018-10-15\",\n",
       "                \"2018-10-16\",\n",
       "                \"2018-10-17\",\n",
       "                \"2018-10-18\",\n",
       "                \"2018-10-19\",\n",
       "                \"2018-10-22\",\n",
       "                \"2018-10-23\",\n",
       "                \"2018-10-24\",\n",
       "                \"2018-10-25\",\n",
       "                \"2018-10-26\",\n",
       "                \"2018-10-29\",\n",
       "                \"2018-10-30\",\n",
       "                \"2018-10-31\",\n",
       "                \"2018-11-01\",\n",
       "                \"2018-11-02\",\n",
       "                \"2018-11-05\",\n",
       "                \"2018-11-06\",\n",
       "                \"2018-11-07\",\n",
       "                \"2018-11-08\",\n",
       "                \"2018-11-09\",\n",
       "                \"2018-11-12\",\n",
       "                \"2018-11-13\",\n",
       "                \"2018-11-14\",\n",
       "                \"2018-11-15\",\n",
       "                \"2018-11-16\",\n",
       "                \"2018-11-19\",\n",
       "                \"2018-11-20\",\n",
       "                \"2018-11-21\",\n",
       "                \"2018-11-22\",\n",
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      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x11487c9e8>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zzhli.v_netvalue()\n",
    "# 指数与基准指数的可视化\n",
    "# 二者都在研究区间的初始日归一"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.01574527073375659, 0.9521439752795914)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zzhli.alpha(), zzhli.beta()  # 计算中证红利指数相对于沪深300的 alpha 和 beta 收益"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9546502342557672"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zzhli.correlation_coefficient(\"2020-01-01\")  # 计算两个指数截止2019年底的相关系数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.2380163305711998, 0.2387765132801344)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zzhli.algorithm_volatility(), zzhli.benchmark_volatility()\n",
    "# 计算中证红利和基准沪深300，截止目前的年化波动率"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0956, 0.082)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zzhli.total_annualized_returns(), zzhli.benchmark_annualized_returns()\n",
    "#  计算中证红利和基准沪深300的年化收益率"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2.1074014053052625, 3.8186585488765177)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zzhli.information_ratio(\"2015-06-01\"), zzhli.sharpe(\"2015-06-01\")\n",
    "# 计算指数截止 2015-06-01 的信息比率和夏普比率"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 简单的研究已就得到了充分的量化数据和可视化\n",
    "* 同时可以轻松得出中证红利可以视为沪深300增强的结论\n",
    "* 以此类推，利用该模块功能的一角，就可 diy 很多好玩的研究"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 基金信息类"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "fgzzhl = xa.fundinfo(\"100032\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "$(element).html(`<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>date</th>\n",
       "      <th>netvalue</th>\n",
       "      <th>comment</th>\n",
       "      <th>totvalue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>2010-01-14</td>\n",
       "      <td>1.410</td>\n",
       "      <td>0.245</td>\n",
       "      <td>1.863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2011-01-19</td>\n",
       "      <td>1.151</td>\n",
       "      <td>0.130</td>\n",
       "      <td>1.718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2012-01-16</td>\n",
       "      <td>0.969</td>\n",
       "      <td>0.026</td>\n",
       "      <td>1.542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2015-01-20</td>\n",
       "      <td>1.385</td>\n",
       "      <td>0.056</td>\n",
       "      <td>2.073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2016-02-02</td>\n",
       "      <td>1.118</td>\n",
       "      <td>0.350</td>\n",
       "      <td>2.167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2017-01-17</td>\n",
       "      <td>1.087</td>\n",
       "      <td>0.300</td>\n",
       "      <td>2.469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2018-01-18</td>\n",
       "      <td>1.215</td>\n",
       "      <td>0.188</td>\n",
       "      <td>2.825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2020-02-28</td>\n",
       "      <td>0.984</td>\n",
       "      <td>0.110</td>\n",
       "      <td>2.689</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>`);\n",
       "\n",
       "                require([\"DT\"], function(DT) {$(document).ready( () => {\n",
       "                    // Turn existing table into datatable\n",
       "                    $(element).find(\"table.dataframe\").DataTable({'scrollX': '100%'});\n",
       "                    })\n",
       "                });\n",
       "        "
      ],
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>netvalue</th>\n",
       "      <th>comment</th>\n",
       "      <th>totvalue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>243</th>\n",
       "      <td>2010-01-14</td>\n",
       "      <td>1.410</td>\n",
       "      <td>0.245</td>\n",
       "      <td>1.863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>488</th>\n",
       "      <td>2011-01-19</td>\n",
       "      <td>1.151</td>\n",
       "      <td>0.130</td>\n",
       "      <td>1.718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>729</th>\n",
       "      <td>2012-01-16</td>\n",
       "      <td>0.969</td>\n",
       "      <td>0.026</td>\n",
       "      <td>1.542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1458</th>\n",
       "      <td>2015-01-20</td>\n",
       "      <td>1.385</td>\n",
       "      <td>0.056</td>\n",
       "      <td>2.073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1712</th>\n",
       "      <td>2016-02-02</td>\n",
       "      <td>1.118</td>\n",
       "      <td>0.350</td>\n",
       "      <td>2.167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1945</th>\n",
       "      <td>2017-01-17</td>\n",
       "      <td>1.087</td>\n",
       "      <td>0.300</td>\n",
       "      <td>2.469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2191</th>\n",
       "      <td>2018-01-18</td>\n",
       "      <td>1.215</td>\n",
       "      <td>0.188</td>\n",
       "      <td>2.825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2701</th>\n",
       "      <td>2020-02-28</td>\n",
       "      <td>0.984</td>\n",
       "      <td>0.110</td>\n",
       "      <td>2.689</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           date  netvalue  comment  totvalue\n",
       "243  2010-01-14     1.410    0.245     1.863\n",
       "488  2011-01-19     1.151    0.130     1.718\n",
       "729  2012-01-16     0.969    0.026     1.542\n",
       "1458 2015-01-20     1.385    0.056     2.073\n",
       "1712 2016-02-02     1.118    0.350     2.167\n",
       "1945 2017-01-17     1.087    0.300     2.469\n",
       "2191 2018-01-18     1.215    0.188     2.825\n",
       "2701 2020-02-28     0.984    0.110     2.689"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fgzzhl.special  # 发生分红或折算的细节"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "fund name: 富国中证红利指数增强A\n",
      "fund code: 100032\n",
      "fund purchase fee: 0.15%\n",
      "fund redemption fee info: ['小于7天', '1.50%', '大于等于7天', '0.50%']\n"
     ]
    }
   ],
   "source": [
    "fgzzhl.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Timestamp('2010-01-14 00:00:00'),\n",
       " Timestamp('2011-01-19 00:00:00'),\n",
       " Timestamp('2012-01-16 00:00:00'),\n",
       " Timestamp('2015-01-20 00:00:00'),\n",
       " Timestamp('2016-02-02 00:00:00'),\n",
       " Timestamp('2017-01-17 00:00:00'),\n",
       " Timestamp('2018-01-18 00:00:00'),\n",
       " Timestamp('2020-02-28 00:00:00')]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fgzzhl.fenhongdate\n",
    "# 基金分红日期"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fgzzhl.zhesuandate\n",
    "# 该基金未发生过份额折算"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "$(element).html(`<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>date</th>\n",
       "      <th>netvalue</th>\n",
       "      <th>comment</th>\n",
       "      <th>totvalue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>2010-01-14</td>\n",
       "      <td>1.410</td>\n",
       "      <td>0.245</td>\n",
       "      <td>1.863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2011-01-19</td>\n",
       "      <td>1.151</td>\n",
       "      <td>0.130</td>\n",
       "      <td>1.718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2012-01-16</td>\n",
       "      <td>0.969</td>\n",
       "      <td>0.026</td>\n",
       "      <td>1.542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2015-01-20</td>\n",
       "      <td>1.385</td>\n",
       "      <td>0.056</td>\n",
       "      <td>2.073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2016-02-02</td>\n",
       "      <td>1.118</td>\n",
       "      <td>0.350</td>\n",
       "      <td>2.167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2017-01-17</td>\n",
       "      <td>1.087</td>\n",
       "      <td>0.300</td>\n",
       "      <td>2.469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2018-01-18</td>\n",
       "      <td>1.215</td>\n",
       "      <td>0.188</td>\n",
       "      <td>2.825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2020-02-28</td>\n",
       "      <td>0.984</td>\n",
       "      <td>0.110</td>\n",
       "      <td>2.689</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>`);\n",
       "\n",
       "                require([\"DT\"], function(DT) {$(document).ready( () => {\n",
       "                    // Turn existing table into datatable\n",
       "                    $(element).find(\"table.dataframe\").DataTable({'scrollX': '100%'});\n",
       "                    })\n",
       "                });\n",
       "        "
      ],
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>netvalue</th>\n",
       "      <th>comment</th>\n",
       "      <th>totvalue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>243</th>\n",
       "      <td>2010-01-14</td>\n",
       "      <td>1.410</td>\n",
       "      <td>0.245</td>\n",
       "      <td>1.863</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>488</th>\n",
       "      <td>2011-01-19</td>\n",
       "      <td>1.151</td>\n",
       "      <td>0.130</td>\n",
       "      <td>1.718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>729</th>\n",
       "      <td>2012-01-16</td>\n",
       "      <td>0.969</td>\n",
       "      <td>0.026</td>\n",
       "      <td>1.542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1458</th>\n",
       "      <td>2015-01-20</td>\n",
       "      <td>1.385</td>\n",
       "      <td>0.056</td>\n",
       "      <td>2.073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1712</th>\n",
       "      <td>2016-02-02</td>\n",
       "      <td>1.118</td>\n",
       "      <td>0.350</td>\n",
       "      <td>2.167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1945</th>\n",
       "      <td>2017-01-17</td>\n",
       "      <td>1.087</td>\n",
       "      <td>0.300</td>\n",
       "      <td>2.469</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2191</th>\n",
       "      <td>2018-01-18</td>\n",
       "      <td>1.215</td>\n",
       "      <td>0.188</td>\n",
       "      <td>2.825</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2701</th>\n",
       "      <td>2020-02-28</td>\n",
       "      <td>0.984</td>\n",
       "      <td>0.110</td>\n",
       "      <td>2.689</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           date  netvalue  comment  totvalue\n",
       "243  2010-01-14     1.410    0.245     1.863\n",
       "488  2011-01-19     1.151    0.130     1.718\n",
       "729  2012-01-16     0.969    0.026     1.542\n",
       "1458 2015-01-20     1.385    0.056     2.073\n",
       "1712 2016-02-02     1.118    0.350     2.167\n",
       "1945 2017-01-17     1.087    0.300     2.469\n",
       "2191 2018-01-18     1.215    0.188     2.825\n",
       "2701 2020-02-28     0.984    0.110     2.689"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fgzzhl.price[fgzzhl.price[\"date\"].isin(fgzzhl.specialdate)]\n",
    "# 基金产生分红或折算的日期对应的price表格\n",
    "# 其中 comment 栏正数表示每份额分红的金额， 负数表示现在每份额折算的份额数，常见于分级连接基金"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* 同样的和指数类相似，基金类也可以用 .bcmkset() 来设置比较基准，既可以是指数也可以是基金，从而进行多样的量化和可视化分析\n",
    "* 但需要注意的是像这种出现过分红的基金用净值进行分析相当于无复权数据，会出现偏差，即使使用总值栏数据，也未处理分红的得到的现金\n",
    "* 强烈建议使用 policy 模块的 buyandhold 类来处理这种基金的效果分析， 具体细节请参考相关示例"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 虚拟货币基金类"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "除了指数类和基金类，为了方便，还准备了虚拟的货币基金类。\n",
    "需要注意的是真实的货币基金无法用基金类获取，基金类只支持净值法计价的基金。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "vca = xa.cashinfo(interest=0.00012, start=\"2018-01-01\")\n",
    "# 初始化一个日利率 0.00012，建立于 2018 年的货币基金"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>comment</th>\n",
       "      <th>date</th>\n",
       "      <th>netvalue</th>\n",
       "      <th>totvalue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>218</th>\n",
       "      <td>0</td>\n",
       "      <td>2018-08-07</td>\n",
       "      <td>1.026504</td>\n",
       "      <td>1.026504</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     comment       date  netvalue  totvalue\n",
       "218        0 2018-08-07  1.026504  1.026504"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vca.price.iloc[-2:-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('mf', '货币基金')"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vca.code, vca.name\n",
    "# 虚拟货币基金的代码默认为 mf， 名称为货币基金"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "注意：货币基金类也可以作为基准或是标的，进行同上的量化分析"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 真实货币基金类"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "huobi = xa.mfundinfo(\"004331\")  # 拉取真实的货币基金数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "fund name: 太平日日鑫货币B\n",
      "fund code: 004331\n",
      "fund purchase fee: 0%\n"
     ]
    }
   ],
   "source": [
    "huobi.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "huobi.bcmkset(\n",
    "    xa.cashinfo(interest=0.00011), start=\"2017-05-01\"\n",
    ")  # 和一个虚拟的货币基金比较"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.042599999999999999"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "huobi.total_annualized_returns()  # 该货币基金的平均年化是 4.26%"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.94913838927244121"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "huobi.correlation_coefficient()  # 和一个平稳的虚拟货币基金的关联是 0.95"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 增量IO\n",
    "为了提升基金数据的复用率，减少获取数据的时间，也可以开启本地增量 IO 的选项，将数据本地化\n",
    "\n",
    "* csv 格式"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "ioconf = {\n",
    "    \"save\": True,\n",
    "    \"fetch\": True,\n",
    "    \"path\": \"../../../sknife/dataset/\",\n",
    "    \"form\": \"csv\",\n",
    "}\n",
    "# 可以先生成IO的设置字典，save 字段表示每一个info对象会自动将信息本地化，fetch 字段表示初始化时先尝试本地获取，\n",
    "# path 字段是存储的路径和前缀, form 字段表示存储的格式是 csv\n",
    "# 指数，基金和货币基金类都可以使用这种增量更新策略来提速"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "no saved copy of this index\n"
     ]
    }
   ],
   "source": [
    "zzhli = xa.indexinfo(\n",
    "    \"1399922\", **ioconf\n",
    ")  # 如果是 fetch 时还没有存档，会提醒打印消息，之后按原初始化方法获取"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "zzhli = xa.indexinfo(\"1399922\", **ioconf)  # 数据本地化后，对象初始化速度大幅提升"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* sql 格式"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 需要借助 sqlalchemy 库, 实现方式如下\n",
    "from sqlalchemy import create_engine\n",
    "\n",
    "engine = create_engine(\"mysql://user:pass@host/db_name?charset=utf8\")\n",
    "sqlconf = {\"save\": True, \"fetch\": True, \"path\": engine, \"form\": \"sql\"}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "zzhli = xa.indexinfo(\"1399922\", **sqlconf)  # 设定好 sql 选项后，其他部分均和 csv 类似"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "关于本地缓存与增量 IO，推荐新用户直接使用 ``xa.set_backend()`` 界面设定，而不再需要向 info obj 传入参数。\n",
    "set_backend 的支持参数请查阅文档。"
   ]
  }
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